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Affine and quadratic models with many factors and few parameters

Marco Realdon

The European Journal of Finance, Pages: 1 - 28

Swansea University Author: Marco Realdon

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DOI (Published version): 10.1080/1351847x.2019.1701511

Abstract

"Classic" affine and quadratic term structure models in the literature usually have three or four factors and tens of parameters. However affine and quadratic term structure models with many factors and few parameters (MFFP), i.e. with up to twenty factors and with six to seven parameters,...

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Published in: The European Journal of Finance
ISSN: 1351-847X 1466-4364
Published: Informa UK Limited
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URI: https://cronfa.swan.ac.uk/Record/cronfa52889
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first_indexed 2019-11-26T19:13:15Z
last_indexed 2020-09-17T03:15:51Z
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spelling 2019-11-26T17:59:25.8509626 v2 52889 2019-11-26 Affine and quadratic models with many factors and few parameters 5866b5c5cf6e2ffc303c2c417d881bbe Marco Realdon Marco Realdon true false 2019-11-26 BAF "Classic" affine and quadratic term structure models in the literature usually have three or four factors and tens of parameters. However affine and quadratic term structure models with many factors and few parameters (MFFP), i.e. with up to twenty factors and with six to seven parameters, fit and predict US and Euro sovereign yields betterthan "classic" affine and quadratic models. MFFP models also fit the volatility of and the correlations between changes in yields of different maturities better than "classic" models. MFFP models outperform because fewer parameters reduce in sample over-fitting and because more factors give models more flexibility to match yields of different maturities. Among MFFP models, a type of affine model with stochastic volatility is usually preferable to homoschedastic affine models, but for US yields the quadratic model seems preferable among five factor MFFP models. Journal Article The European Journal of Finance 1 28 Informa UK Limited 1351-847X 1466-4364 affine term structure models, quadratic term structure models, discrete time, squared Gaussian shocks, Giacomini-White tests. 0 0 0 0001-01-01 10.1080/1351847x.2019.1701511 COLLEGE NANME Accounting and Finance COLLEGE CODE BAF Swansea University 2019-11-26T17:59:25.8509626 2019-11-26T17:59:25.8509626 Marco Realdon 1 52889__15975__5ab0eb7593324578a4826a393829cf40.pdf papercascades3.pdf 2019-11-26T18:13:09.6524900 Output 229747 application/pdf Accepted Manuscript true 2021-06-30T00:00:00.0000000 true 52889__15979__2091f91b106b43ba94fe3f9b6123a817.pdf Supplementary Material.pdf 2019-11-27T09:59:15.5177008 Output 317561 application/pdf Supplemental material true 2021-06-30T00:00:00.0000000 true
title Affine and quadratic models with many factors and few parameters
spellingShingle Affine and quadratic models with many factors and few parameters
Marco Realdon
title_short Affine and quadratic models with many factors and few parameters
title_full Affine and quadratic models with many factors and few parameters
title_fullStr Affine and quadratic models with many factors and few parameters
title_full_unstemmed Affine and quadratic models with many factors and few parameters
title_sort Affine and quadratic models with many factors and few parameters
author_id_str_mv 5866b5c5cf6e2ffc303c2c417d881bbe
author_id_fullname_str_mv 5866b5c5cf6e2ffc303c2c417d881bbe_***_Marco Realdon
author Marco Realdon
author2 Marco Realdon
format Journal article
container_title The European Journal of Finance
container_start_page 1
institution Swansea University
issn 1351-847X
1466-4364
doi_str_mv 10.1080/1351847x.2019.1701511
publisher Informa UK Limited
document_store_str 1
active_str 0
description "Classic" affine and quadratic term structure models in the literature usually have three or four factors and tens of parameters. However affine and quadratic term structure models with many factors and few parameters (MFFP), i.e. with up to twenty factors and with six to seven parameters, fit and predict US and Euro sovereign yields betterthan "classic" affine and quadratic models. MFFP models also fit the volatility of and the correlations between changes in yields of different maturities better than "classic" models. MFFP models outperform because fewer parameters reduce in sample over-fitting and because more factors give models more flexibility to match yields of different maturities. Among MFFP models, a type of affine model with stochastic volatility is usually preferable to homoschedastic affine models, but for US yields the quadratic model seems preferable among five factor MFFP models.
published_date 0001-01-01T04:05:32Z
_version_ 1763753414971359232
score 11.037581

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